Last updated: 2025-10-25
Checks: 2 0
Knit directory: DTU-code/analysis/
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Unstaged changes:
Modified: README.md
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | e5f6ae5 | Pedro Baldoni | 2025-10-25 | Adding bioRxiv link |
| html | cb8496e | Pedro Baldoni | 2025-09-28 | Build site. |
| Rmd | bb32db1 | Pedro Baldoni | 2025-09-28 | Adding BANDITS results |
| html | e711778 | Pedro Baldoni | 2025-08-27 | Build site. |
| Rmd | 5951235 | Pedro Baldoni | 2025-08-27 | DTU paper revision |
| html | cb83e05 | Pedro Baldoni | 2025-04-08 | Build site. |
| Rmd | 9bbfdca | Pedro Baldoni | 2025-04-08 | Update landing page |
| Rmd | cd0ad9d | Pedro Baldoni | 2024-05-01 | Start workflowr project. |
This website hosts code for the paper “Dividing out quantification uncertainty enables assessment of differential transcript usage with limma and edgeR” by Baldoni et al. (2025), which presents optimized differential transcript usage (DTU) pipelines using the the R/Bioconductor packages edgeR and limma.
The bioRxiv preprint version of the paper can be accessed from https://doi.org/10.1101/2025.04.07.647659.
The presented pipeline builds upon the latest developments of
edgeR and limma with a unified interface via
the diffSplice function. The pipelines make use of divided counts to remove
the RTA-induced dispersion and account for the sparsity from
transcript-level counts. The new diffSplice pipelines
provide greater power, improved efficiency, and improved FDR control
compared to existing specialized DTU methods.
The pages below present the necessary steps to rerun our simulation study and the code used to generate the figures and tables from the main and supplementary texts of the DTU paper.
The pages below present the data pre-processing steps and analysis report of the RNA-seq experiments from the steady-state adult mouse mammary gland (GEO accession GSE227748).